1. Field of the Invention
The present invention relates generally to wireless communication systems, and more particularly, to a method and system for processing a signal in a communication system.
2. Description of the Art
Wireless communication systems employ equalization algorithms in order to minimize the deleterious effects of different types of interference in signals. Time dispersive nature of multipath channel causes InterSymbol Interference (ISI) in signals and Viterbi based equalizers are typically employed in order to remove such ISI. Viterbi equalizer performs Maximum Likelihood Sequence Estimation (MLSE) in the sense that all possible symbol combinations are evaluated for closeness with received symbols, with high efficiency based on a multiple state trellis.
For higher-order modulation schemes like 8 Phase Shift Keying (8PSK), full state MLSE cannot be employed due to the high computational complexity involved. Hence reduced state equalizers such as Decision Feedback Sequence Estimation (DFSE) or Reduced State Sequence Estimation (RSSE) are employed in which few leading taps of Channel Impulse Response (CIR) gets a MLSE treatment while the remaining taps of CIR get an instantaneous decision feedback treatment. In such equalizers, performance loss is inevitable compared to full state MLSE, however loss can be significantly reduced by performing minimum phase prefiltering wherein estimated CIR is transformed to its minimum phase equivalent.
Minimum phase filters are characterized by high energies on the leading taps, and have all their zeros inside unit circle. Compared to all other filters with same magnitude response, minimum phase filters have highest partial energy in leading taps, and so are preferable in certain applications. Minimum-phase transformation is the process by which any filter can be transformed to equivalent minimum phase filter with same magnitude response using all-pass filters. All-pass filters have unity magnitude response and are used only for altering signal phase favorably. In practical systems, estimated CIR is often mixed phase, i.e., some roots are inside unit circle while some are not. By using all-pass filters, mixed phase filters can be transformed to minimum phase if such a filter is useful. Prefiltering involves minimum phase transformation, wherein zeros of the CIR located outside the unit circle are cancelled and reflected onto their conjugate reciprocal locations.
Prefiltering can be performed using one of the following methods—prediction error filter, Minimum Mean Squared Error-Decision feedback Equalization (MMSE-DFE), spectral factorization, or root-finding approach. Spectral factorization is not considered for Enhanced Data rate for Global System for Mobile communications (GSM) Evolution (EDGE) 8PSK equalization due to high computational complexity. Root-finding approach is not used when filter order is high since iterative search algorithms are involved. Feed-forward filter of MMSE-DFE is known to yield a minimum phase filter when infinite length DFE is considered. However, practical implementation constraints do not facilitate usage of MMSE-DFE as a minimum phase prefilter. Hence a prediction error filter is typically employed in conventional EDGE 8PSK equalizers, which identifies a prediction error filter using Levinson-Durbin recursive algorithm on the 1-sided autocorrelation sequence of the CIR.
Co-channel interference (CCI) mitigation has received lot of attention in recent years, as GSM/EDGE Radio Access Network (GERAN) evolution path has taken interference cancellation as one of the key features to improve receiver performance, and in turn spectral efficiency. While efficient single antenna interference cancellation algorithms have been used for real-valued modulation schemes such as Gaussian Minimum Shift Keying (GMSK), dual antenna receivers are required for complex-valued modulation scheme such as 8PSK. Interference cancellation using antenna array is a well-known technique that typically employs a space-time adaptive filter that weighs and combines signals. Feed-forward and feed-back filters are estimated and used, wherein feed-forward filter is used to cancel CCI and ISI identified by feed-back filter is cancelled by subsequent reduced state equalizer.
While linear prediction based prefiltering is optimum in terms of performance and complexity for conventional EDGE 8PSK equalizers, dual antenna receiver calls for an alternate approach. Dual antenna receivers involve high computational complexity due to processing 2 streams of samples from separate antennas. While the interference canceling filter provides huge performance gains, complexity increases considerably compared to conventional equalizers. Since complexity of algorithms is a crucial aspect in dual antenna receivers, algorithms such as minimum phase prefiltering require significant focus.
In light of the above, there is a need for a simplified method for adaptive prefiltering.